DART (Data-driven AiRcraft Trajectory prediction research) addresses the topic “ER-02-2015 - Data Science in ATM” exploring the applicability of data science and complexity science techniques to the ATM domain. DART will deliver understanding on the suitability of applying big data techniques for predicting multiple correlated aircraft trajectories based on data-driven models and accounting for ATM network complexity effects.
DART will blend computer science non-ATM specific expertise from University of Piraeus Research Center (UPRC, Greece) and Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. (FRHF, Germany) and ATM state of the art and business needs knowledge from Centro de Referencia de Investigación, Desarrollo e Innovación (CRIDA, Spain) and Boeing Research and Technology Europe (BR&T-E, Spain) in a two years long effort.
Data Science is being pervasively applied to many businesses today has even make room for provoking proposals like the now famous form Anderson, Chris: "The end of theory: The Data Deluge Makes the Scientific Method Obsolete." Wired magazine 16.7 (2008): 16-07. DART aims to avoid this hype and present to the ATM community an understanding on what can be achieved today in trajectory prediction using data-driven models.

Keywords: air traffic control, trajectory prediction, data analytics

Notice: The DART project is currently under development. Publication of all the material and results related to this work is limited due to IPR limitations, until the last stages of the project by the end of 2017. Any material that is accessible here is granted under the terms of the copyright notice included in this page.